"FlyReflect: Joint Flying IRS Trajectory and Phase Shift Design Using Deep ..."

Thanh Phung Truong et al. (2023)

> Home

Details and statistics

DOI: 10.1109/JIOT.2022.3218740

access: closed

type: Journal Article

metadata version: 2023-10-31

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/iotj/TruongTDC23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/iotj/TruongTDC23
Thanh Phung Truong, Van-Dat Tuong, Nhu-Ngoc Dao, Sungrae Cho:
FlyReflect: Joint Flying IRS Trajectory and Phase Shift Design Using Deep Reinforcement Learning. IEEE Internet Things J. 10(5): 4605-4620 (2023)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.